Together with Marc Sarazin and Martin Rehm, I’m co-organizing a session on “Networks for Learning” at the upcoming 3rd European Conference on Social Networks (EUSN).

Abstract

This session focuses on papers that use social network analysis to understand how individuals  involved in activities related to education and learning (pupils, students, teachers, school
management, policy makers etc.) are affected by or use their social networks for educational purposes or in educational settings. The session’s papers will build on the assumption that actors are embedded within social networks which provide opportunities and constraints, in turn affecting individuals’ behaviours and attitudes (Monge & Contractor, 2003, Emirbayer & Goodwin, 1994, Borgatti & Halgin, 2011). Within this framework, the session welcomes papers that seek to make empirical, methodological and/or theoretical contributions to understandings of social networks in learning and education. These could include papers on:

• The importance of social networks for the social and learning environments of students (Heidler et al., 2014) and educational professionals (e.g. teachers) (e.g. Rehm & Notten,
  2016a,b)
• Theoretical processes underlying social networks, as well as the antecedents and consequences of networks (e.g. Rehm, 2016)
• Discussions of the particularities of educational settings from a social network perspective
• Methodological innovations for studying social networks in learning and education (e.g. algorithms to describe and explain social and learning environments, combinations of
  different methodological approaches (e.g. Domínguez & Hollstein, 2014; Froehlich, 2016), etc.)
• Social networks of educational policy-makers (e.g. Ball & Junemann, 2012, Rhodes, 2000)
• Other topics within the above remit

Contributions from all fields (Education, Sociology, Computational Social Science, Psychology, Organisation Science, Anthropology, Statistics, etc.) are welcome, including interdisciplinary
endeavours combining insights from educational or learning sciences with social network perspectives. The session welcomes research using qualitative, quantitative, and mixed methods.